Understanding Nonfarm Payroll Dr. Raymond Stone Principle of Stone & McCarthy Research Associates April 9, 2008

Nonfarm Payroll Futures & Options John W. Labuszewski

Outline A Culture of Innovation Significance of NFPs Forecast Error Contract Specifications

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Nonfarm Payrolls (NFP) … NFPs (generally) released at 7:30 am on 1 st Friday of each month by Bureau of Labor Statistics (BLS) BLS generates 2 reports … (i) Establishment Survey of ~375,000 businesses used for NFPs; (ii) Household Survey of ~60,000 households used for unemployment rate Focus on Establishment Survey and seasonally adjusted change in NFPs Nonfarm payrolls (NFPs) represent the most significant of domestic economic indicators FOMC keenly regards NFPs as (generally) the first economic release that provides information regarding economic activity in previous month Note that FOMC’s mission is to balance inflation risks with goal of maximum possible stable growth and employment BUT … no way to gain direct exposure to NFPs Until now … contract launches April 27, 2008 based on May 2, 2008 release Significance of NFPs

Impact of NFPs on Eurodollar futures … Significance of NFPs

Impact of NFPs on Eurodollar futures … Significance of NFPs

Impact of NFPs on Eurodollar futures … Significance of NFPs

Ranking major economic releases … Significance of NFPs Economic IndicatorBriefing.com Rating Non-Farm Payrolls (NFP)A Institute for Supply Mgt (ISM) IndexA- Retail SalesA- Consumer Price Index (CPI)B+ Chicago Purchasing Managers Index (PMI)B Durable OrdersB Gross Domestic Product (GDP)B Philadelphia Fed IndexB Consumer ConfidenceB- Housing Starts and Building PermitsB- Industrial ProductionB- Non-Manufacturing ISM IndexB- Producer Price Index (PPI)B- …

Measuring forecast error From Jan-00 to Jan-08 in thousands of jobs … Forecast Error ConsensusActualDifference 1/31/ /31/ /30/ /31/ /30/ /31/ /31/ /30/ /31/ /30/ /31/ /28/ /31/ /31/ /30/ … Average=70.4 Std Dev=60.6 Maximum=318 Minimum=2

Nonfarm Payroll futures and options … Contract Specifications FuturesOptions Contract Size $25 x change in Total Nonfarm Payrolls (NFPs) as published by BLS One (1) futures contract Quote Quoted in 1,000s, e.g., May 2007 contract would have settled at +157, or change in NFPs (in 000s) from April to May Minimum tick of 1 point (1,000 jobs) = $25 Quoted in 500 jobs or minimum fluctuation of 0.5 (=$12.50) MonthsAll monthly NFP releases, listed on the Monday after the previous month’s release HoursOffered on CME Globex® on Sundays-Thursdays from 5:00 p.m. to 4:00 p.m. CT Last Day Trading in an expiring contract concludes at 7:25 a.m. CT on the first Friday of the contract month or such other day on which NFP figures are scheduled to be released by the BLS Final Settlement Settled in cash to change in seasonally adjusted total NFPs reported by U.S. Dept. of Labor, Bureau of Labor Statistics Table B-1., Employees on nonfarm payrolls by industry sector and selected industry detail, seasonally adjusted change in total NFPs for month prior to named month American style options may be exercised into one (1) futures contract Strike Prices Na 10 point (or 10,000 jobs) intervals from -500,000 to +500,000 jobs Price Limit Price limit of ±200 points (200,000 jobs = $5,000) applied to final settlement price from previous business day’s settlement price Movement in value effectively limited by futures price limit

Understanding Nonfarm Payroll Dr. Raymond Stone

Research has revealed that the U.S. Nonfarm Payroll Numbers have the most profound impact of all high frequency economic reports on not only the U.S. debt markets, but also upon foreign sovereign bond markets. See: What Moves Sovereign Bond Markets? The Effects of Economic News on U.S. and German Yields, (Goldberg and Leonard) Current Issues in Economics and Finance, September 2003, Federal Reserve Bank of New York

Actually the monthly Employment Report includes data from two separate surveys: Household Survey—A survey of roundly 60,000 households. The “Unemployment Rate” is compiled from this survey. Establishment Survey (or Payroll Survey)— Captures payroll counts from roundly 330,000 business and governmental establishments. From this survey the monthly change in Nonfarm Payrolls is estimated.

Why do markets place such enormous emphasis on the payroll data? Timing —usually released the first Friday of the month, capturing employment conditions of the prior month. Comprehensive — providing significant industry specific detail regarding payrolls, hours worked, and earnings.

Payroll data serve as important inputs into other key macroeconomic data. Personal Income—Wages & Salaries, the largest component of PI, are derived from the earnings data from the establishment survey. Industrial Production—Production-worker hours account for nearly ½ of the input to the monthly IP report. Productivity—Hours worked serve as the denominator in the Productivity equation: Productivity = Output/Hours Unit Labor Costs—Earnings serve as the basis for computing compensation costs.

More Generally, Payrolls Tend to be Aligned with other Measures of Macro-activity

How Does the BLS Estimate Payrolls? The three components: (1) Sample-Based Estimate (2) Births/Deaths Estimate (3) Seasonal Adjustment Estimate

Sample-Based Estimate Sample of roundly 300,000 private sector and 30,000 public sector establishments. Survey is based on the pay-period that includes the 12 th of the month. Only respondents that report in consecutive months are included. Typical response rate for the first estimate of payrolls is around 66%.

More than ½ of the responses are collected by touch-tone data entry (TDE) or via computer assisted telephone interviews (CATI).

The BLS uses a “Probability-Based Sample” to correct for differences between the sample and the universe. For example, small firms are under-represented, but BLS corrects for this by assigning higher weights to these firms.

Payroll survey is skewed towards larger firms

Births/Deaths Model (BDM) The BLS’s sample cannot account for new firms (Births) or firms going out of business (Deaths). As a consequence, the sample-based estimate of payrolls would typically understate payroll growth. To account for this shortfall the BLS employs a time-series model to provide current estimates of net payroll changes associated with Births and Deaths of businesses

The BDM tends to render a recurring pattern of estimated net payroll changes associated with Births and Deaths of firms— The so-called “BDM adjustment” is added to the sample- based estimate of payrolls

Because the BDM is a “Times-Series Model” it doesn’t do well in picking up turns or inflection points in the underlying series. During economic downturns or slowdowns the BDM adjustments tend to add too many jobs During periods of economic acceleration the BDM adjustment may understate net new jobs associated with Births and Deaths of firms

Once a year the BLS realigns its monthly estimate to a less timely but more comprehensive accounting of payrolls (unemployment insurance records)..This is the “Benchmark Revision”

Seasonally Adjusting The Payroll Data Not An Easy Task

Another Estimate of Payrolls ADP National Employment Report (issued the Wednesday before the BLS release)

Approaches Used to Forecast Payrolls Model-Based approach—recession models using Initial Unemployment Claims, ISM Employment Indices, etc as independent variables Naïve or Adaptive approach—typically based on the extension of recent trends: looking at moving averages, etc. Judgmental—combines model based, adaptive, weather considerations, and a variety of other factors in developing a payroll forecast

Evolution of Market Expectations Estimates of the next payroll release begin to surface about 2 weeks prior to the report. Estimates tend to be revised based on incoming data, including the Thursday release of Initial Unemployment Insurance Claims. Estimates are further revised by the Employment Indexes from the ISM Manufacturing (1 st business day of month) and the ISM Non- manufacturing reports (3 rd business day). The ADP National Employment Report (Wednesday prior to BLS release) often tends to either reshape or reaffirm market estimates.

Forecasters do better in some months than others

Over the past 10-years Forecasters have mostly over-shot Payrolls

About 2/3rds of all Forecasting Errors are within + or – 100,000

Often Weather Related Swings Account for Forecasting Errors

Forecasting Errors Exhibit a Pattern Similar to the Business Cycle

Some Forecasters Do Better Than Others, But Over Time the Median Forecast Has Out- Performed All Forecasters in the Sample

Understanding Nonfarm Payroll Dr. Raymond Stone Principle of Stone & McCarthy Research Associates April 9, 2008